English RobertaForSequenceClassification Cased model (from ElKulako)

Description

Pretrained RobertaForSequenceClassification model, adapted from Hugging Face and curated to provide scalability and production-readiness using Spark NLP. cryptobert is a English model originally trained by ElKulako.

Predicted Entities

Bearish, Neutral, Bullish

Live Demo Open in Colab Download Copy S3 URI

How to use

documentAssembler = DocumentAssembler() \
    .setInputCol("text") \
    .setOutputCol("document")

tokenizer = Tokenizer() \
    .setInputCols("document") \
    .setOutputCol("token")

seq_classifier = RoBertaForSequenceClassification.pretrained("roberta_classifier_cryptobert","en") \
    .setInputCols(["document", "token"]) \
    .setOutputCol("class")

pipeline = Pipeline(stages=[documentAssembler, tokenizer, seq_classifier])

data = spark.createDataFrame([["PUT YOUR STRING HERE"]]).toDF("text")

result = pipeline.fit(data).transform(data)

val documentAssembler = new DocumentAssembler()
      .setInputCols(Array("text"))
      .setOutputCols(Array("document"))

val tokenizer = new Tokenizer()
    .setInputCols("document")
    .setOutputCol("token")

val seq_classifier = RoBertaForSequenceClassification.pretrained("roberta_classifier_cryptobert","en")
    .setInputCols(Array("document", "token"))
    .setOutputCol("class")

val pipeline = new Pipeline().setStages(Array(documentAssembler, tokenizer, seq_classifier))

val data = Seq("PUT YOUR STRING HERE").toDS.toDF("text")

val result = pipeline.fit(data).transform(data)

import nlu
nlu.load("en.classify.roberta.crypto.").predict("""PUT YOUR STRING HERE""")

Model Information

References

References

• https://huggingface.co/ElKulako/cryptobert
• https://t.me/binanceexchange
• https://t.me/BittrexGlobalEnglish
• https://t.me/huobiglobalofficial
• https://t.me/Kucoin_Exchange
• https://t.me/OKExOfficial_English
• https://www.kaggle.com/datasets/aagghh/crypto-telegram-groups
• https://www.kaggle.com/datasets/paul92s/bitcoin-tweets-14m